Analysis of the Combined Riverine, Pluvial and Coastal Flood Risks in Saint Lucia

Coastal environments are commonly affected by storm surges, which can penetrate river systems and cause excessive flooding in low-lying zones. The passage of low-pressure tropical storms, as the main drivers of storm surges in many regions around the world, can also generate heavy rainfalls in coastal regions. The resulting combination of riverine, pluvial and coastal flooding may cause significant losses and damages particularly in densely-populated areas. The Island of Saint Lucia, located in the Caribbean Sea, is susceptible to flooding caused by heavy rainfalls (such as the torrential rainfall occurred on 24 December 2013), high levels of water in rivers, and storm surges (caused by hurricanes; such as hurricane Tomas in 2010). In this study, we set up and calibrate two 2D hydrodynamic models (LISFLOOD-FP and HEC-RAS-v5) to simulate flood inundation extents caused by these contributing factors. Analyses are based on high-resolution Light Detection and Ranging (LiDAR) terrain data which can better capture flow pathways in urban areas. The inundation models are forced with storm tides generated from a circulation model using parameters from the hurricane database IBTrACs and tidal sea levels from FES2014 (Finite Element Solution) Global Tide Model. Rainfall data from gauges and Integrated Multi-satellite Retrievals for GPM (IMERGE) product is utilized to simulate pluvial flooding. Discharge of rivers is estimated and included in the models for simulating riverine flooding. The inundation models are validated using available satellite imagery. Four experiments are conducted and include: a) Streamflow and Storm Tides; b) Streamflow and Precipitation; c) Precipitation and Storm Tides; d) Streamflow, Storm Tides, and Precipitation. Results show that coupled modelling of multiple factors can cause significant flood impacts, compared to the individual occurrence of each event, and lead to more accurate flood extents. Remotely sensed data provides significant information on flood inundation extents to validate hydrodynamic models particularly in data scarce regions. Areas prone to be affected by severe flooding in St. Lucia include existing infrastructure (such as airports), coastal urban areas, and the communities along the rivers and coastline, which necessitates effective flood mitigation measures.